{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\au283697\Desktop\FPA Log.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}15 Aug 2019, 16:01:23

{com}. do "C:\Users\au283697\Desktop\2\FPA DO FILE Winning Hearts.do"
{txt}
{com}. *Bringing up the dataset.
. 
. use "C:\Dataset_Winning_Hearts"
{txt}
{com}. 
. *age
. codebook Q101

{txt}{hline}
{res}Q101{right:How old are you?}
{txt}{hline}

{col 19}type:  numeric ({res}double{txt})

{col 18}range:  [{res}18{txt},{res}997{txt}]{col 55}units:  {res}1
{col 10}{txt}unique values:  {res}50{col 51}{txt}missing .:  {res}0{txt}/{res}1,000

{txt}{col 19}mean:{res}{col 26}  69.726
{txt}{col 15}std. dev:{res}{col 26} 177.107

{txt}{col 12}percentiles:{col 32}10%{col 42}25%{col 52}50%{col 62}75%{col 72}90%
{res}{col 27}      21{col 37}      26{col 47}      35{col 57}      47{col 67}      57
{txt}
{com}. tabulate Q101

{txt}How old are {c |}
       you? {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
         18 {c |}{res}         19        1.90        1.90
{txt}         19 {c |}{res}         20        2.00        3.90
{txt}         20 {c |}{res}         28        2.80        6.70
{txt}         21 {c |}{res}         43        4.30       11.00
{txt}         22 {c |}{res}         39        3.90       14.90
{txt}         23 {c |}{res}         26        2.60       17.50
{txt}         24 {c |}{res}         29        2.90       20.40
{txt}         25 {c |}{res}         36        3.60       24.00
{txt}         26 {c |}{res}         31        3.10       27.10
{txt}         27 {c |}{res}         35        3.50       30.60
{txt}         28 {c |}{res}         35        3.50       34.10
{txt}         29 {c |}{res}         27        2.70       36.80
{txt}         30 {c |}{res}         32        3.20       40.00
{txt}         31 {c |}{res}         21        2.10       42.10
{txt}         32 {c |}{res}         23        2.30       44.40
{txt}         33 {c |}{res}         22        2.20       46.60
{txt}         34 {c |}{res}         18        1.80       48.40
{txt}         35 {c |}{res}         41        4.10       52.50
{txt}         36 {c |}{res}         22        2.20       54.70
{txt}         37 {c |}{res}         25        2.50       57.20
{txt}         38 {c |}{res}         22        2.20       59.40
{txt}         39 {c |}{res}         18        1.80       61.20
{txt}         40 {c |}{res}         22        2.20       63.40
{txt}         41 {c |}{res}         19        1.90       65.30
{txt}         42 {c |}{res}         22        2.20       67.50
{txt}         43 {c |}{res}         19        1.90       69.40
{txt}         44 {c |}{res}         16        1.60       71.00
{txt}         45 {c |}{res}         15        1.50       72.50
{txt}         46 {c |}{res}         13        1.30       73.80
{txt}         47 {c |}{res}         19        1.90       75.70
{txt}         48 {c |}{res}         22        2.20       77.90
{txt}         49 {c |}{res}          6        0.60       78.50
{txt}         50 {c |}{res}         16        1.60       80.10
{txt}         51 {c |}{res}         19        1.90       82.00
{txt}         52 {c |}{res}         19        1.90       83.90
{txt}         53 {c |}{res}         14        1.40       85.30
{txt}         54 {c |}{res}          8        0.80       86.10
{txt}         55 {c |}{res}          6        0.60       86.70
{txt}         56 {c |}{res}         18        1.80       88.50
{txt}         57 {c |}{res}         16        1.60       90.10
{txt}         58 {c |}{res}          9        0.90       91.00
{txt}         59 {c |}{res}         10        1.00       92.00
{txt}         60 {c |}{res}         17        1.70       93.70
{txt}         61 {c |}{res}          6        0.60       94.30
{txt}         62 {c |}{res}          5        0.50       94.80
{txt}         63 {c |}{res}          8        0.80       95.60
{txt}         64 {c |}{res}          5        0.50       96.10
{txt}         65 {c |}{res}          3        0.30       96.40
{txt}         77 {c |}{res}          1        0.10       96.50
{txt}        997 {c |}{res}         35        3.50      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      1,000      100.00
{txt}
{com}. mvdecode Q101, mv(997)
        {txt}Q101:{res}{col 15}35{txt} missing values generated

{com}. 
. *sex
. codebook Q102

{txt}{hline}
{res}Q102{right:Are you a man or a woman?}
{txt}{hline}

{col 19}type:  numeric ({res}double{txt})
{ralign 22:label}:  {res:Q102}

{col 18}range:  [{res}1{txt},{res}2{txt}]{col 55}units:  {res}1
{col 10}{txt}unique values:  {res}2{col 51}{txt}missing .:  {res}0{txt}/{res}1,000

{txt}{col 13}tabulation:  Freq.   Numeric  Label
{col 21}{res}       516{col 33}       1{col 43}{txt}Man
{col 21}{res}       484{col 33}       2{col 43}{txt}Woman

{com}. tabulate Q102

 {txt}Are you a man or a {c |}
             woman? {c |}      Freq.     Percent        Cum.
{hline 20}{c +}{hline 35}
                Man {c |}{res}        516       51.60       51.60
{txt}              Woman {c |}{res}        484       48.40      100.00
{txt}{hline 20}{c +}{hline 35}
              Total {c |}{res}      1,000      100.00
{txt}
{com}. 
. *education
. codebook Q103

{txt}{hline}
{res}Q103{right:What is the highest level of education you have completed?}
{txt}{hline}

{col 19}type:  numeric ({res}double{txt})
{ralign 22:label}:  {res:Q103}

{col 18}range:  [{res}3{txt},{res}988{txt}]{col 55}units:  {res}1
{col 10}{txt}unique values:  {res}8{col 51}{txt}missing .:  {res}0{txt}/{res}1,000

{txt}{col 13}tabulation:  Freq.   Numeric  Label
{col 21}{res}         2{col 33}       3{col 43}{txt}Complete primary school
{col 21}{res}        16{col 33}       4{col 43}{txt}Incomplete secondary school:
{col 43}technical/vocational type
{col 21}{res}        27{col 33}       5{col 43}{txt}Complete secondary school:
{col 43}technical/vocational type
{col 21}{res}         6{col 33}       6{col 43}{txt}Incomplete secondary school:
{col 43}university-preparatory type
{col 21}{res}        88{col 33}       7{col 43}{txt}Complete secondary school:
{col 43}university-preparatory type
{col 21}{res}       193{col 33}       8{col 43}{txt}Some university-level education,
{col 43}without degree
{col 21}{res}       667{col 33}       9{col 43}{txt}University-level education, with
{col 43}degree
{col 21}{res}         1{col 33}     988{col 43}{txt}Prefer not to state

{com}. tabulate Q103, nolabel

{txt}What is the {c |}
    highest {c |}
   level of {c |}
  education {c |}
   you have {c |}
 completed? {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          3 {c |}{res}          2        0.20        0.20
{txt}          4 {c |}{res}         16        1.60        1.80
{txt}          5 {c |}{res}         27        2.70        4.50
{txt}          6 {c |}{res}          6        0.60        5.10
{txt}          7 {c |}{res}         88        8.80       13.90
{txt}          8 {c |}{res}        193       19.30       33.20
{txt}          9 {c |}{res}        667       66.70       99.90
{txt}        988 {c |}{res}          1        0.10      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      1,000      100.00
{txt}
{com}. mvdecode Q103, mv(988)
        {txt}Q103:{res}{col 15}1{txt} missing value generated

{com}. 
. *state of residence
. codebook Q104

{txt}{hline}
{res}Q104{right:In what state do you currently live?}
{txt}{hline}

{col 19}type:  numeric ({res}double{txt})
{ralign 22:label}:  {res:Q104}

{col 18}range:  [{res}1{txt},{res}25{txt}]{col 55}units:  {res}1
{col 10}{txt}unique values:  {res}25{col 51}{txt}missing .:  {res}0{txt}/{res}1,000

{txt}{ralign 23: examples:}{col 26}{res}4{col 32}{txt}Anzo�tegui
{ralign 23: }{col 26}{res}9{col 32}{txt}Carabobo
{ralign 23: }{col 26}{res}14{col 32}{txt}Lara
{ralign 23: }{col 26}{res}20{col 32}{txt}Sucre

{com}. tabulate Q104, nolabel

    {txt}In what {c |}
   state do {c |}
        you {c |}
  currently {c |}
      live? {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        182       18.20       18.20
{txt}          2 {c |}{res}          1        0.10       18.30
{txt}          3 {c |}{res}          2        0.20       18.50
{txt}          4 {c |}{res}         70        7.00       25.50
{txt}          5 {c |}{res}          8        0.80       26.30
{txt}          6 {c |}{res}         56        5.60       31.90
{txt}          7 {c |}{res}         15        1.50       33.40
{txt}          8 {c |}{res}         60        6.00       39.40
{txt}          9 {c |}{res}         95        9.50       48.90
{txt}         10 {c |}{res}          5        0.50       49.40
{txt}         11 {c |}{res}          2        0.20       49.60
{txt}         12 {c |}{res}         20        2.00       51.60
{txt}         13 {c |}{res}         14        1.40       53.00
{txt}         14 {c |}{res}         95        9.50       62.50
{txt}         15 {c |}{res}         18        1.80       64.30
{txt}         16 {c |}{res}         63        6.30       70.60
{txt}         17 {c |}{res}         26        2.60       73.20
{txt}         18 {c |}{res}         25        2.50       75.70
{txt}         19 {c |}{res}         30        3.00       78.70
{txt}         20 {c |}{res}         30        3.00       81.70
{txt}         21 {c |}{res}         37        3.70       85.40
{txt}         22 {c |}{res}         13        1.30       86.70
{txt}         23 {c |}{res}          5        0.50       87.20
{txt}         24 {c |}{res}         15        1.50       88.70
{txt}         25 {c |}{res}        113       11.30      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      1,000      100.00
{txt}
{com}. tabulate Q104

{txt}In what state do you {c |}
     currently live? {c |}      Freq.     Percent        Cum.
{hline 21}{c +}{hline 35}
    Capital district {c |}{res}        182       18.20       18.20
{txt}Federal dependencies {c |}{res}          1        0.10       18.30
{txt}            Amazonas {c |}{res}          2        0.20       18.50
{txt}          Anzo�tegui {c |}{res}         70        7.00       25.50
{txt}               Apure {c |}{res}          8        0.80       26.30
{txt}              Aragua {c |}{res}         56        5.60       31.90
{txt}             Barinas {c |}{res}         15        1.50       33.40
{txt}             Bolivar {c |}{res}         60        6.00       39.40
{txt}            Carabobo {c |}{res}         95        9.50       48.90
{txt}             Cojedes {c |}{res}          5        0.50       49.40
{txt}       Delta Amacuro {c |}{res}          2        0.20       49.60
{txt}              Falc�n {c |}{res}         20        2.00       51.60
{txt}             Gu�rico {c |}{res}         14        1.40       53.00
{txt}                Lara {c |}{res}         95        9.50       62.50
{txt}              M�rida {c |}{res}         18        1.80       64.30
{txt}             Miranda {c |}{res}         63        6.30       70.60
{txt}             Monagas {c |}{res}         26        2.60       73.20
{txt}       Nueva Esparta {c |}{res}         25        2.50       75.70
{txt}          Portuguesa {c |}{res}         30        3.00       78.70
{txt}               Sucre {c |}{res}         30        3.00       81.70
{txt}             T�chira {c |}{res}         37        3.70       85.40
{txt}            Trujillo {c |}{res}         13        1.30       86.70
{txt}              Vargas {c |}{res}          5        0.50       87.20
{txt}             Yaracuy {c |}{res}         15        1.50       88.70
{txt}               Zulia {c |}{res}        113       11.30      100.00
{txt}{hline 21}{c +}{hline 35}
               Total {c |}{res}      1,000      100.00
{txt}
{com}. 
. *political orientation left vs. right
. codebook Q105

{txt}{hline}
{res}Q105{right:In politics, people normally speak of """"left"""" and """"right"""". On a scale}
{txt}{hline}

{col 19}type:  numeric ({res}double{txt})
{ralign 22:label}:  {res:Q105}

{col 18}range:  [{res}1{txt},{res}988{txt}]{col 55}units:  {res}1
{col 10}{txt}unique values:  {res}12{col 51}{txt}missing .:  {res}0{txt}/{res}1,000

{txt}{ralign 23: examples:}{col 26}{res}6{col 32}{txt}5
{ralign 23: }{col 26}{res}7{col 32}{txt}6
{ralign 23: }{col 26}{res}9{col 32}{txt}8
{ralign 23: }{col 26}{res}11{col 32}{txt}10 = Right

{com}. tabulate Q105, nolabel

         {txt}In {c |}
  politics, {c |}
     people {c |}
   normally {c |}
   speak of {c |}
""""left""" {c |}
      " and {c |}
""""right"" {c |}
   "". On a {c |}
      scale {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}         50        5.00        5.00
{txt}          2 {c |}{res}          9        0.90        5.90
{txt}          3 {c |}{res}         11        1.10        7.00
{txt}          4 {c |}{res}         25        2.50        9.50
{txt}          5 {c |}{res}         20        2.00       11.50
{txt}          6 {c |}{res}        269       26.90       38.40
{txt}          7 {c |}{res}         64        6.40       44.80
{txt}          8 {c |}{res}        120       12.00       56.80
{txt}          9 {c |}{res}        108       10.80       67.60
{txt}         10 {c |}{res}         47        4.70       72.30
{txt}         11 {c |}{res}        226       22.60       94.90
{txt}        988 {c |}{res}         51        5.10      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      1,000      100.00
{txt}
{com}. mvdecode Q105, mv(988)
        {txt}Q105:{res}{col 15}51{txt} missing values generated

{com}. tabulate Q105

{txt}In politics, people {c |}
  normally speak of {c |}
   """"left"""" and {c |}
""""right"""". On a {c |}
              scale {c |}      Freq.     Percent        Cum.
{hline 20}{c +}{hline 35}
           0 = Left {c |}{res}         50        5.27        5.27
{txt}                  1 {c |}{res}          9        0.95        6.22
{txt}                  2 {c |}{res}         11        1.16        7.38
{txt}                  3 {c |}{res}         25        2.63       10.01
{txt}                  4 {c |}{res}         20        2.11       12.12
{txt}                  5 {c |}{res}        269       28.35       40.46
{txt}                  6 {c |}{res}         64        6.74       47.21
{txt}                  7 {c |}{res}        120       12.64       59.85
{txt}                  8 {c |}{res}        108       11.38       71.23
{txt}                  9 {c |}{res}         47        4.95       76.19
{txt}         10 = Right {c |}{res}        226       23.81      100.00
{txt}{hline 20}{c +}{hline 35}
              Total {c |}{res}        949      100.00
{txt}
{com}. 
. *opinion about president Maduro
. codebook Q106

{txt}{hline}
{res}Q106{right:Please tell us if you have a very favorable, somewhat favorable, somewhat unfavo}
{txt}{hline}

{col 19}type:  numeric ({res}double{txt})
{ralign 22:label}:  {res:Q106}

{col 18}range:  [{res}1{txt},{res}988{txt}]{col 55}units:  {res}1
{col 10}{txt}unique values:  {res}5{col 51}{txt}missing .:  {res}0{txt}/{res}1,000

{txt}{col 13}tabulation:  Freq.   Numeric  Label
{col 21}{res}        38{col 33}       1{col 43}{txt}Very favorable
{col 21}{res}        70{col 33}       2{col 43}{txt}Somewhat favorable
{col 21}{res}       153{col 33}       3{col 43}{txt}Somewhat unfavorable
{col 21}{res}       688{col 33}       4{col 43}{txt}Very unfavorable
{col 21}{res}        51{col 33}     988{col 43}{txt}Prefer not to state

{com}. mvdecode Q106, mv(988)
        {txt}Q106:{res}{col 15}51{txt} missing values generated

{com}. tabulate Q106

   {txt}Please tell us if {c |}
     you have a very {c |}
 favorable, somewhat {c |}
 favorable, somewhat {c |}
              unfavo {c |}      Freq.     Percent        Cum.
{hline 21}{c +}{hline 35}
      Very favorable {c |}{res}         38        4.00        4.00
{txt}  Somewhat favorable {c |}{res}         70        7.38       11.38
{txt}Somewhat unfavorable {c |}{res}        153       16.12       27.50
{txt}    Very unfavorable {c |}{res}        688       72.50      100.00
{txt}{hline 21}{c +}{hline 35}
               Total {c |}{res}        949      100.00
{txt}
{com}. 
. *support president's government or opposition
. codebook Q107

{txt}{hline}
{res}Q107{right:In politics, people normally speak of the """"government"""" and the """"opposit}
{txt}{hline}

{col 19}type:  numeric ({res}double{txt})
{ralign 22:label}:  {res:Q107}

{col 18}range:  [{res}1{txt},{res}988{txt}]{col 55}units:  {res}1
{col 10}{txt}unique values:  {res}3{col 51}{txt}missing .:  {res}0{txt}/{res}1,000

{txt}{col 13}tabulation:  Freq.   Numeric  Label
{col 21}{res}        93{col 33}       1{col 43}{txt}I support the government of
{col 43}President Maduro
{col 21}{res}       593{col 33}       2{col 43}{txt}I support the opposition
{col 21}{res}       314{col 33}     988{col 43}{txt}Prefer not to state

{com}. mvdecode Q107, mv(988)
        {txt}Q107:{res}{col 15}314{txt} missing values generated

{com}. tabulate Q107,

  {txt}In politics, people normally speak of {c |}
         the """"government"""" and the {c |}
                            """"opposit {c |}      Freq.     Percent        Cum.
{hline 40}{c +}{hline 35}
I support the government of President M {c |}{res}         93       13.56       13.56
{txt}               I support the opposition {c |}{res}        593       86.44      100.00
{txt}{hline 40}{c +}{hline 35}
                                  Total {c |}{res}        686      100.00
{txt}
{com}. 
. *Knowledge of sanctions.
. codebook Q51

{txt}{hline}
{res}Q51{right:When did you first hear about the U.S. sanctions?}
{txt}{hline}

{col 19}type:  numeric ({res}double{txt})
{ralign 22:label}:  {res:Q51}

{col 18}range:  [{res}1{txt},{res}988{txt}]{col 55}units:  {res}1
{col 10}{txt}unique values:  {res}5{col 51}{txt}missing .:  {res}0{txt}/{res}1,000

{txt}{col 13}tabulation:  Freq.   Numeric  Label
{col 21}{res}       467{col 33}       1{col 43}{txt}More than a year ago
{col 21}{res}       171{col 33}       2{col 43}{txt}Between six and twelve months
{col 43}ago
{col 21}{res}       292{col 33}       3{col 43}{txt}Within the last six months
{col 21}{res}        20{col 33}       4{col 43}{txt}I have never previously heard of
{col 43}this
{col 21}{res}        50{col 33}     988{col 43}{txt}Prefer not to state

{com}. tabulate Q51, nolabel

   {txt}When did {c |}
  you first {c |}
 hear about {c |}
   the U.S. {c |}
 sanctions? {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        467       46.70       46.70
{txt}          2 {c |}{res}        171       17.10       63.80
{txt}          3 {c |}{res}        292       29.20       93.00
{txt}          4 {c |}{res}         20        2.00       95.00
{txt}        988 {c |}{res}         50        5.00      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      1,000      100.00
{txt}
{com}. mvdecode Q51, mv(988)
         {txt}Q51:{res}{col 15}50{txt} missing values generated

{com}. 
. *------------------------------------------------------------------.
. *data trimming.
. *creating new dependent var, numeric variables with highscore = positive.
. 
. gen sfav1 = Q48_version1
{txt}(747 missing values generated)

{com}. gen sfav2 = Q48_version2
{txt}(756 missing values generated)

{com}. gen sfav3 = Q48_version3
{txt}(750 missing values generated)

{com}. gen sfav4 = Q48_version4
{txt}(747 missing values generated)

{com}. mvdecode sfav1, mv(988)
       {txt}sfav1:{res}{col 15}15{txt} missing values generated

{com}. mvdecode sfav2, mv(988)
       {txt}sfav2:{res}{col 15}14{txt} missing values generated

{com}. mvdecode sfav3, mv(988)
       {txt}sfav3:{res}{col 15}9{txt} missing values generated

{com}. mvdecode sfav4, mv(988)
       {txt}sfav4:{res}{col 15}12{txt} missing values generated

{com}. 
. *creating dep variable with answer to any scenario, removing missing.
. 
. gen sfav = max(sfav1, sfav2, sfav3, sfav4) if missing(sfav1, sfav2, sfav3, sfav4)
{txt}(50 missing values generated)

{com}. 
. recode sfav(988=.)
{txt}(sfav: 0 changes made)

{com}. 
. table sfav

{txt}{hline 10}{c TT}{hline 11}
     sfav {c |}      Freq.
{hline 10}{c +}{hline 11}
        1 {c |}        {res}101
        {txt}2 {c |}         {res}51
        {txt}3 {c |}         {res}32
        {txt}4 {c |}        {res}142
        {txt}5 {c |}         {res}54
        {txt}6 {c |}        {res}174
        {txt}7 {c |}        {res}396
{txt}{hline 10}{c BT}{hline 11}

{com}. 
. *creating variable: sank against maduro or Venezuela?. 1 = Maduro.
. recode Q48_split(2 4=0)(1 3=1), gen(maduro)
{txt}(747 differences between Q48_split and maduro)

{com}. label variable maduro "Maduro (vs. Venezuela)"
{txt}
{com}. gen madurocop = maduro
{txt}
{com}. label variable madurocop "Maduro (vs. Venezuela)"
{txt}
{com}. 
. recode Q48_split(2 4=1)(1 3=0), gen(venezuela) 
{txt}(1000 differences between Q48_split and venezuela)

{com}. 
. *creating variable: sank to stop violence or threat against US. 1 = violence.
. recode Q48_split (1 2=1)(3 4=0), gen(violence)
{txt}(747 differences between Q48_split and violence)

{com}. label variable violence "Violence (vs. Threat to the USA)"
{txt}
{com}. gen violencecop = violence
{txt}
{com}. label variable violencecop "Violence(vs. Threat to the USA)"
{txt}
{com}. 
. recode Q48_split (1 2=1)(3 4=0), gen(threat)
{txt}(747 differences between Q48_split and threat)

{com}. 
. *rescaling variables.
. sum sfav

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 8}sfav {c |}{res}        950    5.213684    2.068282          1          7
{txt}
{com}. gen supsa = (sfav - r(min)) / (r(max) - r(min))
{txt}(50 missing values generated)

{com}. sum Q102

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 8}Q102 {c |}{res}      1,000       1.484     .499994          1          2
{txt}
{com}. gen fem = (Q102 - r(min)) / (r(max) - r(min))
{txt}
{com}. sum Q103

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 8}Q103 {c |}{res}        999    8.412412    1.077222          3          9
{txt}
{com}. gen uni = (Q103 - r(min)) / (r(max) - r(min))
{txt}(1 missing value generated)

{com}. recode Q104(1=1)(else=0), gen(loc)
{txt}(818 differences between Q104 and loc)

{com}. sum Q105

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 8}Q105 {c |}{res}        949    7.640674    2.712775          1         11
{txt}
{com}. gen left = (Q105 - r(min)) / (r(max) - r(min))
{txt}(51 missing values generated)

{com}. sum Q106

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 8}Q106 {c |}{res}        949    3.571128    .7958548          1          4
{txt}
{com}. gen reg = (Q106 - r(min)) / (r(max) - r(min))
{txt}(51 missing values generated)

{com}. sum Q107

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 8}Q107 {c |}{res}        686    1.864431    .3425796          1          2
{txt}
{com}. gen opp = (Q107 - r(min)) / (r(max) - r(min))
{txt}(314 missing values generated)

{com}. sum Q51

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 9}Q51 {c |}{res}        950    1.857895    .9294479          1          4
{txt}
{com}. gen kno = (Q51 - r(min)) / (r(max) - r(min))
{txt}(50 missing values generated)

{com}. 
. *Table 2.
. summarize sfav

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 8}sfav {c |}{res}        950    5.213684    2.068282          1          7
{txt}
{com}. summarize Q101

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 8}Q101 {c |}{res}        965     36.0943    12.46981         18         77
{txt}
{com}. summarize Q102

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 8}Q102 {c |}{res}      1,000       1.484     .499994          1          2
{txt}
{com}. summarize Q103

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 8}Q103 {c |}{res}        999    8.412412    1.077222          3          9
{txt}
{com}. summarize Q104

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 8}Q104 {c |}{res}      1,000      11.813    8.004755          1         25
{txt}
{com}. summarize Q105

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 8}Q105 {c |}{res}        949    7.640674    2.712775          1         11
{txt}
{com}. summarize Q106

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 8}Q106 {c |}{res}        949    3.571128    .7958548          1          4
{txt}
{com}. summarize Q107

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 8}Q107 {c |}{res}        686    1.864431    .3425796          1          2
{txt}
{com}. 
. *Table 3.
. *manipulation check: age, gender, education, location, left-right.
. *political position, government or opposition.
. 
. recode Q48_split(1=1)(2 3 4=0), gen(mpc1)
{txt}(747 differences between Q48_split and mpc1)

{com}. 
. recode Q48_split(2=1)(1 3 4=0), gen(mpc2)
{txt}(1000 differences between Q48_split and mpc2)

{com}. 
. recode Q48_split(3=1)(1 2 4=0), gen(mpc3)
{txt}(1000 differences between Q48_split and mpc3)

{com}. 
. recode Q48_split(4=1)(1 2 3=0), gen(mpc4)
{txt}(1000 differences between Q48_split and mpc4)

{com}. 
. mean Q101
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       965

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 8}Q101 {c |}{col 14}{res}{space 2}  36.0943{col 26}{space 2} .4014175{col 37}{space 5} 35.30655{col 51}{space 3} 36.88205
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean Q101 if mpc1==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       243

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 8}Q101 {c |}{col 14}{res}{space 2} 36.39918{col 26}{space 2} .7976204{col 37}{space 5} 34.82801{col 51}{space 3} 37.97034
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean Q101 if mpc2==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       234

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 8}Q101 {c |}{col 14}{res}{space 2} 35.41453{col 26}{space 2} .8441826{col 37}{space 5} 33.75132{col 51}{space 3} 37.07774
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean Q101 if mpc3==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       246

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 8}Q101 {c |}{col 14}{res}{space 2} 36.40244{col 26}{space 2} .7693218{col 37}{space 5} 34.88711{col 51}{space 3} 37.91777
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean Q101 if mpc4==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       242

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 8}Q101 {c |}{col 14}{res}{space 2} 36.13223{col 26}{space 2} .8051241{col 37}{space 5} 34.54625{col 51}{space 3} 37.71821
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean fem
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}     1,000

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}fem {c |}{col 14}{res}{space 2}     .484{col 26}{space 2} .0158112{col 37}{space 5}  .452973{col 51}{space 3}  .515027
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean fem if mpc1==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       253

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}fem {c |}{col 14}{res}{space 2} .4980237{col 26}{space 2} .0314968{col 37}{space 5} .4359932{col 51}{space 3} .5600542
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean fem if mpc2==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       244

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}fem {c |}{col 14}{res}{space 2} .5204918{col 26}{space 2} .0320481{col 37}{space 5} .4573643{col 51}{space 3} .5836193
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean fem if mpc3==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       250

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}fem {c |}{col 14}{res}{space 2}     .476{col 26}{space 2} .0316497{col 37}{space 5} .4136648{col 51}{space 3} .5383352
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean fem if mpc4==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       253

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}fem {c |}{col 14}{res}{space 2} .4426877{col 26}{space 2} .0312894{col 37}{space 5} .3810656{col 51}{space 3} .5043099
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean uni
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       999

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}uni {c |}{col 14}{res}{space 2} .9020687{col 26}{space 2} .0056803{col 37}{space 5}  .890922{col 51}{space 3} .9132154
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean uni if mpc1==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       253

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}uni {c |}{col 14}{res}{space 2}  .897892{col 26}{space 2} .0120639{col 37}{space 5} .8741331{col 51}{space 3} .9216508
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean uni if mpc2==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       243

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}uni {c |}{col 14}{res}{space 2}   .89369{col 26}{space 2} .0115032{col 37}{space 5} .8710308{col 51}{space 3} .9163492
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean uni if mpc3==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       250

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}uni {c |}{col 14}{res}{space 2} .9086667{col 26}{space 2} .0108933{col 37}{space 5}  .887212{col 51}{space 3} .9301213
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean uni if mpc4==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       253

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}uni {c |}{col 14}{res}{space 2} .9077734{col 26}{space 2} .0109764{col 37}{space 5} .8861563{col 51}{space 3} .9293905
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean loc
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}     1,000

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}loc {c |}{col 14}{res}{space 2}     .182{col 26}{space 2} .0122076{col 37}{space 5} .1580446{col 51}{space 3} .2059554
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean loc if mpc1==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       253

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}loc {c |}{col 14}{res}{space 2}  .229249{col 26}{space 2} .0264795{col 37}{space 5} .1770996{col 51}{space 3} .2813984
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean loc if mpc2==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       244

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}loc {c |}{col 14}{res}{space 2} .1885246{col 26}{space 2}  .025091{col 37}{space 5} .1391009{col 51}{space 3} .2379483
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean loc if mpc3==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       250

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}loc {c |}{col 14}{res}{space 2}     .132{col 26}{space 2}  .021451{col 37}{space 5} .0897515{col 51}{space 3} .1742485
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean loc if mpc4==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       253

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}loc {c |}{col 14}{res}{space 2} .1778656{col 26}{space 2} .0240889{col 37}{space 5} .1304244{col 51}{space 3} .2253068
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean left
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       949

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 8}left {c |}{col 14}{res}{space 2} .6640674{col 26}{space 2}  .008806{col 37}{space 5} .6467859{col 51}{space 3}  .681349
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean left if mpc1==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       246

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 8}left {c |}{col 14}{res}{space 2} .6520325{col 26}{space 2} .0176775{col 37}{space 5} .6172133{col 51}{space 3} .6868518
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean left if mpc2==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       233

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 8}left {c |}{col 14}{res}{space 2} .6686695{col 26}{space 2} .0175984{col 37}{space 5} .6339965{col 51}{space 3} .7033426
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean left if mpc3==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       234

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 8}left {c |}{col 14}{res}{space 2} .6709402{col 26}{space 2} .0167421{col 37}{space 5} .6379549{col 51}{space 3} .7039254
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean left if mpc4==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       236

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 8}left {c |}{col 14}{res}{space 2} .6652542{col 26}{space 2} .0184384{col 37}{space 5} .6289285{col 51}{space 3}   .70158
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean reg
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       949

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}reg {c |}{col 14}{res}{space 2} .8570425{col 26}{space 2} .0086115{col 37}{space 5} .8401427{col 51}{space 3} .8739423
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean reg if mpc1==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       246

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}reg {c |}{col 14}{res}{space 2} .8631436{col 26}{space 2}  .016492{col 37}{space 5} .8306595{col 51}{space 3} .8956277
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean reg if mpc2==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       232

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}reg {c |}{col 14}{res}{space 2} .8548851{col 26}{space 2} .0167319{col 37}{space 5} .8219185{col 51}{space 3} .8878516
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean reg if mpc3==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       236

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}reg {c |}{col 14}{res}{space 2} .8615819{col 26}{space 2} .0163423{col 37}{space 5} .8293859{col 51}{space 3}  .893778
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean reg if mpc4==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       235

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}reg {c |}{col 14}{res}{space 2}  .848227{col 26}{space 2} .0192964{col 37}{space 5}   .81021{col 51}{space 3} .8862439
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean opp
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       686

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}opp {c |}{col 14}{res}{space 2} .8644315{col 26}{space 2} .0130797{col 37}{space 5} .8387503{col 51}{space 3} .8901127
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean opp if mpc1==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       176

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}opp {c |}{col 14}{res}{space 2} .8352273{col 26}{space 2} .0280431{col 37}{space 5} .7798811{col 51}{space 3} .8905735
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean opp if mpc2==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       159

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}opp {c |}{col 14}{res}{space 2} .8679245{col 26}{space 2} .0269354{col 37}{space 5} .8147246{col 51}{space 3} .9211244
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean opp if mpc3==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       170

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}opp {c |}{col 14}{res}{space 2} .8764706{col 26}{space 2} .0253111{col 37}{space 5}  .826504{col 51}{space 3} .9264372
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. mean opp if mpc4==1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       181

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}opp {c |}{col 14}{res}{space 2}  .878453{col 26}{space 2} .0243554{col 37}{space 5} .8303942{col 51}{space 3} .9265118
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. *Table 4.
. tabulate Q48_split, summarize(supsa)

  {txt}Q48 Split {c |}          Summary of supsa
     Sample {c |}        Mean   Std. Dev.       Freq.
{hline 12}{c +}{hline 36}
  Version 1 {c |}  {res} .79131653   .31131083         238
  {txt}Version 2 {c |}  {res} .68913043   .34457424         230
  {txt}Version 3 {c |}  {res} .70539419   .34274686         241
  {txt}Version 4 {c |}  {res} .62378976   .35940566         241
{txt}{hline 12}{c +}{hline 36}
      Total {c |}  {res}  .7022807   .34471362         950
{txt}
{com}. 
. *--------------------------------------------------------------------------------
. *Table 5.
. *experiment.
. reg supsa maduro violence

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       950
{txt}{hline 13}{c +}{hline 34}   F(2, 947)       = {res}    14.67
{txt}       Model {c |} {res} 3.38844302         2  1.69422151   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 109.378836       947  .115500355   {txt}R-squared       ={res}    0.0300
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0280
{txt}       Total {c |} {res} 112.767279       949  .118827481   {txt}Root MSE        =   {res} .33985

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       supsa{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}maduro {c |}{col 14}{res}{space 2} .0917421{col 26}{space 2} .0220542{col 37}{space 1}    4.16{col 46}{space 3}0.000{col 54}{space 4} .0484614{col 67}{space 3} .1350228
{txt}{space 4}violence {c |}{col 14}{res}{space 2} .0757208{col 26}{space 2} .0220558{col 37}{space 1}    3.43{col 46}{space 3}0.001{col 54}{space 4} .0324369{col 67}{space 3} .1190047
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .6187209{col 26}{space 2} .0190059{col 37}{space 1}   32.55{col 46}{space 3}0.000{col 54}{space 4} .5814224{col 67}{space 3} .6560195
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg supsa maduro violence Q101 Q102 Q103 Q104 Q105 Q106 Q107

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       634
{txt}{hline 13}{c +}{hline 34}   F(9, 624)       = {res}    54.19
{txt}       Model {c |} {res} 31.6420549         9  3.51578387   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 40.4818489       624  .064874758   {txt}R-squared       ={res}    0.4387
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.4306
{txt}       Total {c |} {res} 72.1239038       633  .113939816   {txt}Root MSE        =   {res} .25471

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       supsa{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}maduro {c |}{col 14}{res}{space 2} .0918209{col 26}{space 2} .0204178{col 37}{space 1}    4.50{col 46}{space 3}0.000{col 54}{space 4}  .051725{col 67}{space 3} .1319167
{txt}{space 4}violence {c |}{col 14}{res}{space 2}   .10648{col 26}{space 2}  .020363{col 37}{space 1}    5.23{col 46}{space 3}0.000{col 54}{space 4} .0664917{col 67}{space 3} .1464682
{txt}{space 8}Q101 {c |}{col 14}{res}{space 2} .0015172{col 26}{space 2} .0008132{col 37}{space 1}    1.87{col 46}{space 3}0.063{col 54}{space 4}-.0000797{col 67}{space 3} .0031142
{txt}{space 8}Q102 {c |}{col 14}{res}{space 2}-.0101932{col 26}{space 2} .0206685{col 37}{space 1}   -0.49{col 46}{space 3}0.622{col 54}{space 4}-.0507813{col 67}{space 3}  .030395
{txt}{space 8}Q103 {c |}{col 14}{res}{space 2} .0192046{col 26}{space 2}   .01052{col 37}{space 1}    1.83{col 46}{space 3}0.068{col 54}{space 4}-.0014543{col 67}{space 3} .0398634
{txt}{space 8}Q104 {c |}{col 14}{res}{space 2} .0020464{col 26}{space 2} .0012512{col 37}{space 1}    1.64{col 46}{space 3}0.102{col 54}{space 4}-.0004107{col 67}{space 3} .0045036
{txt}{space 8}Q105 {c |}{col 14}{res}{space 2} .0082294{col 26}{space 2} .0040417{col 37}{space 1}    2.04{col 46}{space 3}0.042{col 54}{space 4} .0002923{col 67}{space 3} .0161665
{txt}{space 8}Q106 {c |}{col 14}{res}{space 2} .0386346{col 26}{space 2} .0172383{col 37}{space 1}    2.24{col 46}{space 3}0.025{col 54}{space 4} .0047826{col 67}{space 3} .0724867
{txt}{space 8}Q107 {c |}{col 14}{res}{space 2} .5202969{col 26}{space 2} .0443415{col 37}{space 1}   11.73{col 46}{space 3}0.000{col 54}{space 4} .4332201{col 67}{space 3} .6073736
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-.7532819{col 26}{space 2} .1078906{col 37}{space 1}   -6.98{col 46}{space 3}0.000{col 54}{space 4}-.9651546{col 67}{space 3}-.5414092
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg supsa i.maduro##i.violence

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       950
{txt}{hline 13}{c +}{hline 34}   F(3, 946)       = {res}     9.84
{txt}       Model {c |} {res} 3.41358537         3  1.13786179   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 109.353694       946  .115595871   {txt}R-squared       ={res}    0.0303
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0272
{txt}       Total {c |} {res} 112.767279       949  .118827481   {txt}Root MSE        =   {res} .33999

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          supsa{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}1.maduro {c |}{col 17}{res}{space 2} .0816044{col 29}{space 2} .0309726{col 40}{space 1}    2.63{col 49}{space 3}0.009{col 57}{space 4} .0208215{col 70}{space 3} .1423874
{txt}{space 5}1.violence {c |}{col 17}{res}{space 2} .0653407{col 29}{space 2} .0313407{col 40}{space 1}    2.08{col 49}{space 3}0.037{col 57}{space 4} .0038353{col 70}{space 3} .1268461
{txt}{space 15} {c |}
maduro#violence {c |}
{space 11}1 1  {c |}{col 17}{res}{space 2} .0205817{col 29}{space 2} .0441315{col 40}{space 1}    0.47{col 49}{space 3}0.641{col 57}{space 4}-.0660253{col 70}{space 3} .1071886
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} .6237898{col 29}{space 2} .0219009{col 40}{space 1}   28.48{col 49}{space 3}0.000{col 57}{space 4} .5808097{col 70}{space 3} .6667698
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg supsa i.maduro##i.violence Q101 Q102 Q103 Q104 Q105 Q106 Q107

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       634
{txt}{hline 13}{c +}{hline 34}   F(10, 623)      = {res}    48.78
{txt}       Model {c |} {res} 31.6728387        10  3.16728387   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 40.4510651       623  .064929478   {txt}R-squared       ={res}    0.4391
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.4301
{txt}       Total {c |} {res} 72.1239038       633  .113939816   {txt}Root MSE        =   {res} .25481

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          supsa{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}1.maduro {c |}{col 17}{res}{space 2} .0782818{col 29}{space 2} .0283526{col 40}{space 1}    2.76{col 49}{space 3}0.006{col 57}{space 4} .0226036{col 70}{space 3}   .13396
{txt}{space 5}1.violence {c |}{col 17}{res}{space 2} .0922229{col 29}{space 2}  .029047{col 40}{space 1}    3.17{col 49}{space 3}0.002{col 57}{space 4}  .035181{col 70}{space 3} .1492648
{txt}{space 15} {c |}
maduro#violence {c |}
{space 11}1 1  {c |}{col 17}{res}{space 2} .0280131{col 29}{space 2} .0406837{col 40}{space 1}    0.69{col 49}{space 3}0.491{col 57}{space 4}-.0518807{col 70}{space 3} .1079069
{txt}{space 15} {c |}
{space 11}Q101 {c |}{col 17}{res}{space 2} .0015001{col 29}{space 2} .0008139{col 40}{space 1}    1.84{col 49}{space 3}0.066{col 57}{space 4}-.0000983{col 70}{space 3} .0030985
{txt}{space 11}Q102 {c |}{col 17}{res}{space 2}-.0104698{col 29}{space 2} .0206811{col 40}{space 1}   -0.51{col 49}{space 3}0.613{col 57}{space 4}-.0510829{col 70}{space 3} .0301433
{txt}{space 11}Q103 {c |}{col 17}{res}{space 2} .0189519{col 29}{space 2} .0105308{col 40}{space 1}    1.80{col 49}{space 3}0.072{col 57}{space 4}-.0017283{col 70}{space 3} .0396321
{txt}{space 11}Q104 {c |}{col 17}{res}{space 2} .0020799{col 29}{space 2} .0012527{col 40}{space 1}    1.66{col 49}{space 3}0.097{col 57}{space 4}-.0003801{col 70}{space 3} .0045399
{txt}{space 11}Q105 {c |}{col 17}{res}{space 2} .0083749{col 29}{space 2}  .004049{col 40}{space 1}    2.07{col 49}{space 3}0.039{col 57}{space 4} .0004236{col 70}{space 3} .0163262
{txt}{space 11}Q106 {c |}{col 17}{res}{space 2} .0387162{col 29}{space 2} .0172459{col 40}{space 1}    2.24{col 49}{space 3}0.025{col 57}{space 4}  .004849{col 70}{space 3} .0725834
{txt}{space 11}Q107 {c |}{col 17}{res}{space 2} .5200578{col 29}{space 2} .0443616{col 40}{space 1}   11.72{col 49}{space 3}0.000{col 57}{space 4} .4329414{col 70}{space 3} .6071742
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}-.7449175{col 29}{space 2} .1086176{col 40}{space 1}   -6.86{col 49}{space 3}0.000{col 57}{space 4}-.9582184{col 70}{space 3}-.5316166
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. *Table 8.
. *ordered logit experiments.
. ologit supsa maduro violence

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-1550.6368}  
Iteration 1:{space 3}log likelihood = {res:-1532.2677}  
Iteration 2:{space 3}log likelihood = {res:-1532.2418}  
Iteration 3:{space 3}log likelihood = {res:-1532.2418}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}       950
{txt}{col 49}LR chi2({res}2{txt}){col 67}= {res}     36.79
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-1532.2418{txt}{col 49}Pseudo R2{col 67}= {res}    0.0119

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       supsa{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}maduro {c |}{col 14}{res}{space 2} .5473433{col 26}{space 2} .1188682{col 37}{space 1}    4.60{col 46}{space 3}0.000{col 54}{space 4}  .314366{col 67}{space 3} .7803207
{txt}{space 4}violence {c |}{col 14}{res}{space 2} .4638002{col 26}{space 2} .1186994{col 37}{space 1}    3.91{col 46}{space 3}0.000{col 54}{space 4} .2311536{col 67}{space 3} .6964467
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}/cut1 {c |}{col 14}{res}{space 2}-1.677408{col 26}{space 2} .1279901{col 54}{space 4}-1.928264{col 67}{space 3}-1.426552
{txt}{space 7}/cut2 {c |}{col 14}{res}{space 2}-1.200284{col 26}{space 2} .1154799{col 54}{space 4}-1.426621{col 67}{space 3}-.9739479
{txt}{space 7}/cut3 {c |}{col 14}{res}{space 2} -.964448{col 26}{space 2} .1112092{col 54}{space 4}-1.182414{col 67}{space 3} -.746482
{txt}{space 7}/cut4 {c |}{col 14}{res}{space 2}-.1726112{col 26}{space 2} .1040012{col 54}{space 4}-.3764499{col 67}{space 3} .0312275
{txt}{space 7}/cut5 {c |}{col 14}{res}{space 2}  .077016{col 26}{space 2} .1035915{col 54}{space 4}-.1260195{col 67}{space 3} .2800515
{txt}{space 7}/cut6 {c |}{col 14}{res}{space 2} .8428776{col 26}{space 2} .1073337{col 54}{space 4} .6325073{col 67}{space 3} 1.053248
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. ologit supsa maduro violence Q101 Q102 Q103 Q104 Q105 Q106 Q107

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-955.64848}  
Iteration 1:{space 3}log likelihood = {res:-832.10175}  
Iteration 2:{space 3}log likelihood = {res:-814.73832}  
Iteration 3:{space 3}log likelihood = {res:-812.57546}  
Iteration 4:{space 3}log likelihood = {res:-812.57047}  
Iteration 5:{space 3}log likelihood = {res:-812.57047}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}       634
{txt}{col 49}LR chi2({res}9{txt}){col 67}= {res}    286.16
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-812.57047{txt}{col 49}Pseudo R2{col 67}= {res}    0.1497

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       supsa{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}maduro {c |}{col 14}{res}{space 2}  .744629{col 26}{space 2} .1598376{col 37}{space 1}    4.66{col 46}{space 3}0.000{col 54}{space 4} .4313531{col 67}{space 3} 1.057905
{txt}{space 4}violence {c |}{col 14}{res}{space 2} .9180329{col 26}{space 2} .1613891{col 37}{space 1}    5.69{col 46}{space 3}0.000{col 54}{space 4}  .601716{col 67}{space 3}  1.23435
{txt}{space 8}Q101 {c |}{col 14}{res}{space 2} .0127289{col 26}{space 2}  .006407{col 37}{space 1}    1.99{col 46}{space 3}0.047{col 54}{space 4} .0001715{col 67}{space 3} .0252864
{txt}{space 8}Q102 {c |}{col 14}{res}{space 2}  .011785{col 26}{space 2} .1606449{col 37}{space 1}    0.07{col 46}{space 3}0.942{col 54}{space 4}-.3030732{col 67}{space 3} .3266431
{txt}{space 8}Q103 {c |}{col 14}{res}{space 2} .1393293{col 26}{space 2} .0804523{col 37}{space 1}    1.73{col 46}{space 3}0.083{col 54}{space 4}-.0183543{col 67}{space 3} .2970129
{txt}{space 8}Q104 {c |}{col 14}{res}{space 2} .0105448{col 26}{space 2} .0098167{col 37}{space 1}    1.07{col 46}{space 3}0.283{col 54}{space 4}-.0086955{col 67}{space 3} .0297852
{txt}{space 8}Q105 {c |}{col 14}{res}{space 2} .0767756{col 26}{space 2}  .030691{col 37}{space 1}    2.50{col 46}{space 3}0.012{col 54}{space 4} .0166224{col 67}{space 3} .1369288
{txt}{space 8}Q106 {c |}{col 14}{res}{space 2} .3009128{col 26}{space 2} .1286333{col 37}{space 1}    2.34{col 46}{space 3}0.019{col 54}{space 4} .0487963{col 67}{space 3} .5530294
{txt}{space 8}Q107 {c |}{col 14}{res}{space 2} 2.975179{col 26}{space 2} .3488124{col 37}{space 1}    8.53{col 46}{space 3}0.000{col 54}{space 4} 2.291519{col 67}{space 3} 3.658839
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}/cut1 {c |}{col 14}{res}{space 2}  6.70783{col 26}{space 2} .8653579{col 54}{space 4} 5.011759{col 67}{space 3}   8.4039
{txt}{space 7}/cut2 {c |}{col 14}{res}{space 2} 7.502864{col 26}{space 2}  .876582{col 54}{space 4} 5.784794{col 67}{space 3} 9.220933
{txt}{space 7}/cut3 {c |}{col 14}{res}{space 2} 7.800807{col 26}{space 2} .8820075{col 54}{space 4} 6.072104{col 67}{space 3}  9.52951
{txt}{space 7}/cut4 {c |}{col 14}{res}{space 2} 8.589474{col 26}{space 2} .8987333{col 54}{space 4} 6.827989{col 67}{space 3} 10.35096
{txt}{space 7}/cut5 {c |}{col 14}{res}{space 2} 9.007855{col 26}{space 2} .9064007{col 54}{space 4} 7.231342{col 67}{space 3} 10.78437
{txt}{space 7}/cut6 {c |}{col 14}{res}{space 2} 10.09408{col 26}{space 2} .9218219{col 54}{space 4} 8.287341{col 67}{space 3} 11.90082
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. ologit supsa i.maduro##i.violence

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-1550.6368}  
Iteration 1:{space 3}log likelihood = {res:-1531.8768}  
Iteration 2:{space 3}log likelihood = {res:-1531.8387}  
Iteration 3:{space 3}log likelihood = {res:-1531.8387}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}       950
{txt}{col 49}LR chi2({res}3{txt}){col 67}= {res}     37.60
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-1531.8387{txt}{col 49}Pseudo R2{col 67}= {res}    0.0121

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          supsa{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}1.maduro {c |}{col 17}{res}{space 2} .4475814{col 29}{space 2} .1625727{col 40}{space 1}    2.75{col 49}{space 3}0.006{col 57}{space 4} .1289447{col 70}{space 3} .7662181
{txt}{space 5}1.violence {c |}{col 17}{res}{space 2} .3620832{col 29}{space 2} .1639532{col 40}{space 1}    2.21{col 49}{space 3}0.027{col 57}{space 4} .0407409{col 70}{space 3} .6834256
{txt}{space 15} {c |}
maduro#violence {c |}
{space 11}1 1  {c |}{col 17}{res}{space 2} .2127921{col 29}{space 2} .2370699{col 40}{space 1}    0.90{col 49}{space 3}0.369{col 57}{space 4}-.2518564{col 70}{space 3} .6774406
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}/cut1 {c |}{col 17}{res}{space 2}-1.725346{col 29}{space 2}  .138915{col 57}{space 4}-1.997614{col 70}{space 3}-1.453077
{txt}{space 10}/cut2 {c |}{col 17}{res}{space 2} -1.24853{col 29}{space 2}  .127581{col 57}{space 4}-1.498584{col 70}{space 3}-.9984756
{txt}{space 10}/cut3 {c |}{col 17}{res}{space 2}-1.012892{col 29}{space 2} .1237976{col 57}{space 4}-1.255531{col 70}{space 3}-.7702535
{txt}{space 10}/cut4 {c |}{col 17}{res}{space 2}-.2211222{col 29}{space 2} .1172742{col 57}{space 4}-.4509754{col 70}{space 3} .0087311
{txt}{space 10}/cut5 {c |}{col 17}{res}{space 2} .0287123{col 29}{space 2} .1167726{col 57}{space 4}-.2001577{col 70}{space 3} .2575823
{txt}{space 10}/cut6 {c |}{col 17}{res}{space 2} .7952654{col 29}{space 2} .1196961{col 57}{space 4} .5606654{col 70}{space 3} 1.029865
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. ologit supsa i.maduro##i.violence Q101 Q102 Q103 Q104 Q105 Q106 Q107

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-955.64848}  
Iteration 1:{space 3}log likelihood = {res: -831.7605}  
Iteration 2:{space 3}log likelihood = {res:-814.30129}  
Iteration 3:{space 3}log likelihood = {res:-812.06285}  
Iteration 4:{space 3}log likelihood = {res:-812.05745}  
Iteration 5:{space 3}log likelihood = {res:-812.05745}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}       634
{txt}{col 49}LR chi2({res}10{txt}){col 67}= {res}    287.18
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-812.05745{txt}{col 49}Pseudo R2{col 67}= {res}    0.1503

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          supsa{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}1.maduro {c |}{col 17}{res}{space 2} .6056352{col 29}{space 2} .2102759{col 40}{space 1}    2.88{col 49}{space 3}0.004{col 57}{space 4} .1935019{col 70}{space 3} 1.017768
{txt}{space 5}1.violence {c |}{col 17}{res}{space 2} .7673952{col 29}{space 2} .2188225{col 40}{space 1}    3.51{col 49}{space 3}0.000{col 57}{space 4}  .338511{col 70}{space 3} 1.196279
{txt}{space 15} {c |}
maduro#violence {c |}
{space 11}1 1  {c |}{col 17}{res}{space 2} .3241537{col 29}{space 2} .3203973{col 40}{space 1}    1.01{col 49}{space 3}0.312{col 57}{space 4}-.3038135{col 70}{space 3}  .952121
{txt}{space 15} {c |}
{space 11}Q101 {c |}{col 17}{res}{space 2} .0124906{col 29}{space 2}  .006422{col 40}{space 1}    1.94{col 49}{space 3}0.052{col 57}{space 4}-.0000963{col 70}{space 3} .0250775
{txt}{space 11}Q102 {c |}{col 17}{res}{space 2}  .007577{col 29}{space 2} .1608514{col 40}{space 1}    0.05{col 49}{space 3}0.962{col 57}{space 4}-.3076859{col 70}{space 3} .3228398
{txt}{space 11}Q103 {c |}{col 17}{res}{space 2} .1370597{col 29}{space 2} .0809547{col 40}{space 1}    1.69{col 49}{space 3}0.090{col 57}{space 4}-.0216086{col 70}{space 3}  .295728
{txt}{space 11}Q104 {c |}{col 17}{res}{space 2} .0111592{col 29}{space 2}   .00985{col 40}{space 1}    1.13{col 49}{space 3}0.257{col 57}{space 4}-.0081464{col 70}{space 3} .0304649
{txt}{space 11}Q105 {c |}{col 17}{res}{space 2} .0790613{col 29}{space 2}   .03084{col 40}{space 1}    2.56{col 49}{space 3}0.010{col 57}{space 4}  .018616{col 70}{space 3} .1395066
{txt}{space 11}Q106 {c |}{col 17}{res}{space 2} .3011365{col 29}{space 2}  .127952{col 40}{space 1}    2.35{col 49}{space 3}0.019{col 57}{space 4} .0503552{col 70}{space 3} .5519178
{txt}{space 11}Q107 {c |}{col 17}{res}{space 2} 2.977853{col 29}{space 2} .3484153{col 40}{space 1}    8.55{col 49}{space 3}0.000{col 57}{space 4} 2.294972{col 70}{space 3} 3.660734
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}/cut1 {c |}{col 17}{res}{space 2} 6.640278{col 29}{space 2} .8712108{col 57}{space 4} 4.932737{col 70}{space 3}  8.34782
{txt}{space 10}/cut2 {c |}{col 17}{res}{space 2} 7.438113{col 29}{space 2} .8821899{col 57}{space 4} 5.709053{col 70}{space 3} 9.167173
{txt}{space 10}/cut3 {c |}{col 17}{res}{space 2} 7.736146{col 29}{space 2} .8875513{col 57}{space 4} 5.996578{col 70}{space 3} 9.475715
{txt}{space 10}/cut4 {c |}{col 17}{res}{space 2} 8.524542{col 29}{space 2} .9040855{col 57}{space 4} 6.752567{col 70}{space 3} 10.29652
{txt}{space 10}/cut5 {c |}{col 17}{res}{space 2} 8.942864{col 29}{space 2} .9116539{col 57}{space 4} 7.156055{col 70}{space 3} 10.72967
{txt}{space 10}/cut6 {c |}{col 17}{res}{space 2} 10.02719{col 29}{space 2} .9269008{col 57}{space 4} 8.210496{col 70}{space 3} 11.84388
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *Figure 1.
. mean supsa if maduro == 1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       479

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 7}supsa {c |}{col 14}{res}{space 2} .7480863{col 26}{space 2}  .015077{col 37}{space 5} .7184609{col 51}{space 3} .7777117
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. estimate store madurofig1
{txt}
{com}. gen supsaa = supsa
{txt}(50 missing values generated)

{com}. mean supsaa if maduro == 0
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       471

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 6}supsaa {c |}{col 14}{res}{space 2} .6556971{col 26}{space 2}  .016283{col 37}{space 5} .6237006{col 51}{space 3} .6876936
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. estimate store venezuelafig1
{txt}
{com}. gen supsab = supsa
{txt}(50 missing values generated)

{com}. mean supsab if violence == 1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       468

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 6}supsab {c |}{col 14}{res}{space 2} .7410969{col 26}{space 2} .0153325{col 37}{space 5} .7109676{col 51}{space 3} .7712262
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. estimate store violencefig1
{txt}
{com}. gen supsac = supsa
{txt}(50 missing values generated)

{com}. mean supsac if violence == 0
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       482

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 6}supsac {c |}{col 14}{res}{space 2}  .664592{col 26}{space 2} .0160869{col 37}{space 5} .6329827{col 51}{space 3} .6962012
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. estimate store threatfig1
{txt}
{com}. 
. coefplot (madurofig1) (venezuelafig1) (violencefig1) (threatfig1), graphregion(color(white)) ///
> color(black) ciopts(lcolor(gs0)) mlabcolor(gs0) bgcolor(white) nooffsets mlabel format(%9.2g) ///
> mlabposition(9) vertical legend(off) yscale(r(.6)) ylabel(.6 .7 .8) xscale(r(.2)) grid(none) ///
> rename(supsa = "Maduro" supsaa = "Venezuela" supsab = "Violence" supsac = "Threat") ytitle(Support for sanctions)
{res}{txt}
{com}. 
. *Figure 2.
. reg supsa maduro violence

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       950
{txt}{hline 13}{c +}{hline 34}   F(2, 947)       = {res}    14.67
{txt}       Model {c |} {res} 3.38844302         2  1.69422151   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 109.378836       947  .115500355   {txt}R-squared       ={res}    0.0300
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0280
{txt}       Total {c |} {res} 112.767279       949  .118827481   {txt}Root MSE        =   {res} .33985

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       supsa{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}maduro {c |}{col 14}{res}{space 2} .0917421{col 26}{space 2} .0220542{col 37}{space 1}    4.16{col 46}{space 3}0.000{col 54}{space 4} .0484614{col 67}{space 3} .1350228
{txt}{space 4}violence {c |}{col 14}{res}{space 2} .0757208{col 26}{space 2} .0220558{col 37}{space 1}    3.43{col 46}{space 3}0.001{col 54}{space 4} .0324369{col 67}{space 3} .1190047
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .6187209{col 26}{space 2} .0190059{col 37}{space 1}   32.55{col 46}{space 3}0.000{col 54}{space 4} .5814224{col 67}{space 3} .6560195
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store sanormal
{txt}
{com}. 
. reg supsa i.maduro##i.violence

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       950
{txt}{hline 13}{c +}{hline 34}   F(3, 946)       = {res}     9.84
{txt}       Model {c |} {res} 3.41358537         3  1.13786179   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 109.353694       946  .115595871   {txt}R-squared       ={res}    0.0303
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0272
{txt}       Total {c |} {res} 112.767279       949  .118827481   {txt}Root MSE        =   {res} .33999

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          supsa{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}1.maduro {c |}{col 17}{res}{space 2} .0816044{col 29}{space 2} .0309726{col 40}{space 1}    2.63{col 49}{space 3}0.009{col 57}{space 4} .0208215{col 70}{space 3} .1423874
{txt}{space 5}1.violence {c |}{col 17}{res}{space 2} .0653407{col 29}{space 2} .0313407{col 40}{space 1}    2.08{col 49}{space 3}0.037{col 57}{space 4} .0038353{col 70}{space 3} .1268461
{txt}{space 15} {c |}
maduro#violence {c |}
{space 11}1 1  {c |}{col 17}{res}{space 2} .0205817{col 29}{space 2} .0441315{col 40}{space 1}    0.47{col 49}{space 3}0.641{col 57}{space 4}-.0660253{col 70}{space 3} .1071886
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} .6237898{col 29}{space 2} .0219009{col 40}{space 1}   28.48{col 49}{space 3}0.000{col 57}{space 4} .5808097{col 70}{space 3} .6667698
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store sainteractionx
{txt}
{com}. 
. recode maduro(1=0)(0=1), gen(madurotest)
{txt}(1000 differences between maduro and madurotest)

{com}. recode violence(1=0)(0=1), gen(violencetest)
{txt}(1000 differences between violence and violencetest)

{com}. gen violencex = violence
{txt}
{com}. 
. reg supsa i.madurotest##i.violencex

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       950
{txt}{hline 13}{c +}{hline 34}   F(3, 946)       = {res}     9.84
{txt}       Model {c |} {res} 3.41358537         3  1.13786179   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 109.353694       946  .115595871   {txt}R-squared       ={res}    0.0303
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0272
{txt}       Total {c |} {res} 112.767279       949  .118827481   {txt}Root MSE        =   {res} .33999

{txt}{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}               supsa{col 22}{c |}      Coef.{col 34}   Std. Err.{col 46}      t{col 54}   P>|t|{col 62}     [95% Con{col 75}f. Interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}1.madurotest {c |}{col 22}{res}{space 2}-.0816044{col 34}{space 2} .0309726{col 45}{space 1}   -2.63{col 54}{space 3}0.009{col 62}{space 4}-.1423874{col 75}{space 3}-.0208215
{txt}{space 9}1.violencex {c |}{col 22}{res}{space 2} .0859223{col 34}{space 2}   .03107{col 45}{space 1}    2.77{col 54}{space 3}0.006{col 62}{space 4} .0249482{col 75}{space 3} .1468965
{txt}{space 20} {c |}
madurotest#violencex {c |}
{space 16}1 1  {c |}{col 22}{res}{space 2}-.0205817{col 34}{space 2} .0441315{col 45}{space 1}   -0.47{col 54}{space 3}0.641{col 62}{space 4}-.1071886{col 75}{space 3} .0660253
{txt}{space 20} {c |}
{space 15}_cons {c |}{col 22}{res}{space 2} .7053942{col 34}{space 2} .0219009{col 45}{space 1}   32.21{col 54}{space 3}0.000{col 62}{space 4} .6624142{col 75}{space 3} .7483742
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store sainteractiony
{txt}
{com}. 
. coefplot (sanormal) ///
> , drop(_cons 1.madurotest) ///
> xline(0, lcolor(black) lpattern(dash)) graphregion(color(white)) color(black) ///
> ciopts(lcolor(gs0)) mlabcolor(gs0) bgcolor(white) nooffsets level(90) ///
> xscale(r(-.2 .2)) xlabel(-.2 -.1 0 .1 .2) scale(0.80) ///
> mlabel format(%9.2g) mlabposition(12) grid(none) legend(off)
{res}{txt}
{com}. 
. *experiments and view of the president without controls.
. reg supsa i.Q106##i.maduro i.Q106##i.violence

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       914
{txt}{hline 13}{c +}{hline 34}   F(11, 902)      = {res}    37.45
{txt}       Model {c |} {res} 33.6018346        11  3.05471224   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 73.5809077       902  .081575286   {txt}R-squared       ={res}    0.3135
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.3051
{txt}       Total {c |} {res} 107.182742       913  .117396213   {txt}Root MSE        =   {res} .28561

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                 supsa{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}Q106 {c |}
{space 3}Somewhat favorable  {c |}{col 24}{res}{space 2}-.4234965{col 36}{space 2} .0917341{col 47}{space 1}   -4.62{col 56}{space 3}0.000{col 64}{space 4}-.6035337{col 77}{space 3}-.2434594
{txt}{space 1}Somewhat unfavorable  {c |}{col 24}{res}{space 2}-.2932553{col 36}{space 2} .0809035{col 47}{space 1}   -3.62{col 56}{space 3}0.000{col 64}{space 4}-.4520362{col 77}{space 3}-.1344744
{txt}{space 5}Very unfavorable  {c |}{col 24}{res}{space 2} .1158746{col 36}{space 2} .0697938{col 47}{space 1}    1.66{col 56}{space 3}0.097{col 64}{space 4}-.0211026{col 77}{space 3} .2528518
{txt}{space 22} {c |}
{space 14}1.maduro {c |}{col 24}{res}{space 2} -.193984{col 36}{space 2} .1036412{col 47}{space 1}   -1.87{col 56}{space 3}0.062{col 64}{space 4}  -.39739{col 77}{space 3} .0094219
{txt}{space 22} {c |}
{space 11}Q106#maduro {c |}
{space 1}Somewhat favorable#1  {c |}{col 24}{res}{space 2} .2338146{col 36}{space 2} .1247268{col 47}{space 1}    1.87{col 56}{space 3}0.061{col 64}{space 4}-.0109738{col 77}{space 3}  .478603
{txt}{space 1}Somewhat unfavorable #{c |}
{space 20}1  {c |}{col 24}{res}{space 2} .3385998{col 36}{space 2} .1142596{col 47}{space 1}    2.96{col 56}{space 3}0.003{col 64}{space 4} .1143543{col 77}{space 3} .5628453
{txt}{space 3}Very unfavorable#1  {c |}{col 24}{res}{space 2} .2839755{col 36}{space 2} .1059873{col 47}{space 1}    2.68{col 56}{space 3}0.008{col 64}{space 4} .0759651{col 77}{space 3} .4919859
{txt}{space 22} {c |}
{space 12}1.violence {c |}{col 24}{res}{space 2}-.1597606{col 36}{space 2} .1018132{col 47}{space 1}   -1.57{col 56}{space 3}0.117{col 64}{space 4}-.3595788{col 77}{space 3} .0400577
{txt}{space 22} {c |}
{space 9}Q106#violence {c |}
{space 1}Somewhat favorable#1  {c |}{col 24}{res}{space 2} .2976304{col 36}{space 2}  .123212{col 47}{space 1}    2.42{col 56}{space 3}0.016{col 64}{space 4} .0558149{col 77}{space 3} .5394458
{txt}{space 1}Somewhat unfavorable #{c |}
{space 20}1  {c |}{col 24}{res}{space 2} .2888725{col 36}{space 2}  .112604{col 47}{space 1}    2.57{col 56}{space 3}0.010{col 64}{space 4} .0678761{col 77}{space 3} .5098689
{txt}{space 3}Very unfavorable#1  {c |}{col 24}{res}{space 2} .2257257{col 36}{space 2} .1041989{col 47}{space 1}    2.17{col 56}{space 3}0.031{col 64}{space 4} .0212252{col 77}{space 3} .4302262
{txt}{space 22} {c |}
{space 17}_cons {c |}{col 24}{res}{space 2} .6210866{col 36}{space 2} .0671336{col 47}{space 1}    9.25{col 56}{space 3}0.000{col 64}{space 4} .4893303{col 77}{space 3} .7528428
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. *Table 6 and Table 7.
. *Figure 3.
. reg supsa i.Q106##i.maduro i.Q106##i.violence Q101 Q102 Q103 Q104 Q105

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       861
{txt}{hline 13}{c +}{hline 34}   F(16, 844)      = {res}    30.64
{txt}       Model {c |} {res} 37.3444548        16  2.33402842   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res}  64.282399       844   .07616398   {txt}R-squared       ={res}    0.3675
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.3555
{txt}       Total {c |} {res} 101.626854       860   .11817076   {txt}Root MSE        =   {res} .27598

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                 supsa{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}Q106 {c |}
{space 3}Somewhat favorable  {c |}{col 24}{res}{space 2}-.4407117{col 36}{space 2}  .092391{col 47}{space 1}   -4.77{col 56}{space 3}0.000{col 64}{space 4}-.6220548{col 77}{space 3}-.2593686
{txt}{space 1}Somewhat unfavorable  {c |}{col 24}{res}{space 2}-.2723242{col 36}{space 2} .0795464{col 47}{space 1}   -3.42{col 56}{space 3}0.001{col 64}{space 4}-.4284562{col 77}{space 3}-.1161922
{txt}{space 5}Very unfavorable  {c |}{col 24}{res}{space 2} .1107289{col 36}{space 2} .0683074{col 47}{space 1}    1.62{col 56}{space 3}0.105{col 64}{space 4}-.0233434{col 77}{space 3} .2448012
{txt}{space 22} {c |}
{space 14}1.maduro {c |}{col 24}{res}{space 2}-.1367657{col 36}{space 2} .1042142{col 47}{space 1}   -1.31{col 56}{space 3}0.190{col 64}{space 4} -.341315{col 77}{space 3} .0677837
{txt}{space 22} {c |}
{space 11}Q106#maduro {c |}
{space 1}Somewhat favorable#1  {c |}{col 24}{res}{space 2} .2159583{col 36}{space 2} .1259686{col 47}{space 1}    1.71{col 56}{space 3}0.087{col 64}{space 4}-.0312903{col 77}{space 3} .4632068
{txt}{space 1}Somewhat unfavorable #{c |}
{space 20}1  {c |}{col 24}{res}{space 2} .3041053{col 36}{space 2} .1147473{col 47}{space 1}    2.65{col 56}{space 3}0.008{col 64}{space 4} .0788817{col 77}{space 3} .5293289
{txt}{space 3}Very unfavorable#1  {c |}{col 24}{res}{space 2}  .214311{col 36}{space 2} .1065644{col 47}{space 1}    2.01{col 56}{space 3}0.045{col 64}{space 4} .0051487{col 77}{space 3} .4234732
{txt}{space 22} {c |}
{space 12}1.violence {c |}{col 24}{res}{space 2}-.0792266{col 36}{space 2} .1039555{col 47}{space 1}   -0.76{col 56}{space 3}0.446{col 64}{space 4}-.2832682{col 77}{space 3}  .124815
{txt}{space 22} {c |}
{space 9}Q106#violence {c |}
{space 1}Somewhat favorable#1  {c |}{col 24}{res}{space 2} .2495118{col 36}{space 2} .1253184{col 47}{space 1}    1.99{col 56}{space 3}0.047{col 64}{space 4} .0035395{col 77}{space 3} .4954842
{txt}{space 1}Somewhat unfavorable #{c |}
{space 20}1  {c |}{col 24}{res}{space 2} .1859222{col 36}{space 2} .1144774{col 47}{space 1}    1.62{col 56}{space 3}0.105{col 64}{space 4}-.0387716{col 77}{space 3}  .410616
{txt}{space 3}Very unfavorable#1  {c |}{col 24}{res}{space 2} .1512328{col 36}{space 2} .1061993{col 47}{space 1}    1.42{col 56}{space 3}0.155{col 64}{space 4} -.057213{col 77}{space 3} .3596786
{txt}{space 22} {c |}
{space 18}Q101 {c |}{col 24}{res}{space 2} .0010389{col 36}{space 2} .0007658{col 47}{space 1}    1.36{col 56}{space 3}0.175{col 64}{space 4}-.0004642{col 77}{space 3} .0025419
{txt}{space 18}Q102 {c |}{col 24}{res}{space 2} .0012926{col 36}{space 2} .0191765{col 47}{space 1}    0.07{col 56}{space 3}0.946{col 64}{space 4}-.0363467{col 77}{space 3} .0389319
{txt}{space 18}Q103 {c |}{col 24}{res}{space 2} .0138381{col 36}{space 2} .0090021{col 47}{space 1}    1.54{col 56}{space 3}0.125{col 64}{space 4}-.0038309{col 77}{space 3} .0315072
{txt}{space 18}Q104 {c |}{col 24}{res}{space 2} .0019385{col 36}{space 2} .0011766{col 47}{space 1}    1.65{col 56}{space 3}0.100{col 64}{space 4}-.0003709{col 77}{space 3}  .004248
{txt}{space 18}Q105 {c |}{col 24}{res}{space 2}  .021644{col 36}{space 2} .0037532{col 47}{space 1}    5.77{col 56}{space 3}0.000{col 64}{space 4} .0142772{col 77}{space 3} .0290107
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .2783116{col 36}{space 2} .1060136{col 47}{space 1}    2.63{col 56}{space 3}0.009{col 64}{space 4} .0702303{col 77}{space 3} .4863929
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, dydx(maduro) over(Q106)
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}       861
{txt}Model VCE{col 14}: {res}OLS

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.maduro}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:over}:{space 1}{res:Q106}{p_end}
{p2colreset}{...}

{res}{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35} Delta-method
{col 23}{c |}      dy/dx{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}0.maduro             {col 23}{txt}{c |}  (base outcome)
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}1.maduro              {txt}{c |}
{space 17}Q106 {c |}
{space 6}Very favorable  {c |}{col 23}{res}{space 2}-.1367657{col 35}{space 2} .1042142{col 46}{space 1}   -1.31{col 55}{space 3}0.190{col 63}{space 4} -.341315{col 76}{space 3} .0677837
{txt}{space 2}Somewhat favorable  {c |}{col 23}{res}{space 2} .0791926{col 35}{space 2} .0709253{col 46}{space 1}    1.12{col 55}{space 3}0.264{col 63}{space 4}-.0600181{col 76}{space 3} .2184033
{txt}Somewhat unfavorable  {c |}{col 23}{res}{space 2} .1673396{col 35}{space 2} .0482575{col 46}{space 1}    3.47{col 55}{space 3}0.001{col 63}{space 4} .0726207{col 76}{space 3} .2620585
{txt}{space 4}Very unfavorable  {c |}{col 23}{res}{space 2} .0775453{col 35}{space 2} .0220578{col 46}{space 1}    3.52{col 55}{space 3}0.000{col 63}{space 4} .0342508{col 76}{space 3} .1208398
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 87}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. marginsplot, recast(scatter) yline(0, lcolor(gs0)) xscale(range(0.5 4.5)) xtitle("") title("") ytitle("Maduro effect on support for sanctions") ///
> graphregion(color(white)) xlabel(,labsize(small)) ylabels(-0.4 (0.1) 0.4) level(90) ciopts(lcolor(gs0)) bgcolor(white)
{res}
{text}{p 2 6 2}Variables that uniquely identify margins: Q106{p_end}
{res}{txt}
{com}. 
. reg supsa i.Q106##i.violence i.Q106##i.maduro Q101 Q102 Q103 Q104 Q105

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       861
{txt}{hline 13}{c +}{hline 34}   F(16, 844)      = {res}    30.64
{txt}       Model {c |} {res} 37.3444548        16  2.33402842   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res}  64.282399       844   .07616398   {txt}R-squared       ={res}    0.3675
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.3555
{txt}       Total {c |} {res} 101.626854       860   .11817076   {txt}Root MSE        =   {res} .27598

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                 supsa{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}Q106 {c |}
{space 3}Somewhat favorable  {c |}{col 24}{res}{space 2}-.4407117{col 36}{space 2}  .092391{col 47}{space 1}   -4.77{col 56}{space 3}0.000{col 64}{space 4}-.6220548{col 77}{space 3}-.2593686
{txt}{space 1}Somewhat unfavorable  {c |}{col 24}{res}{space 2}-.2723242{col 36}{space 2} .0795464{col 47}{space 1}   -3.42{col 56}{space 3}0.001{col 64}{space 4}-.4284562{col 77}{space 3}-.1161922
{txt}{space 5}Very unfavorable  {c |}{col 24}{res}{space 2} .1107289{col 36}{space 2} .0683074{col 47}{space 1}    1.62{col 56}{space 3}0.105{col 64}{space 4}-.0233434{col 77}{space 3} .2448012
{txt}{space 22} {c |}
{space 12}1.violence {c |}{col 24}{res}{space 2}-.0792266{col 36}{space 2} .1039555{col 47}{space 1}   -0.76{col 56}{space 3}0.446{col 64}{space 4}-.2832682{col 77}{space 3}  .124815
{txt}{space 22} {c |}
{space 9}Q106#violence {c |}
{space 1}Somewhat favorable#1  {c |}{col 24}{res}{space 2} .2495118{col 36}{space 2} .1253184{col 47}{space 1}    1.99{col 56}{space 3}0.047{col 64}{space 4} .0035395{col 77}{space 3} .4954842
{txt}{space 1}Somewhat unfavorable #{c |}
{space 20}1  {c |}{col 24}{res}{space 2} .1859222{col 36}{space 2} .1144774{col 47}{space 1}    1.62{col 56}{space 3}0.105{col 64}{space 4}-.0387716{col 77}{space 3}  .410616
{txt}{space 3}Very unfavorable#1  {c |}{col 24}{res}{space 2} .1512328{col 36}{space 2} .1061993{col 47}{space 1}    1.42{col 56}{space 3}0.155{col 64}{space 4} -.057213{col 77}{space 3} .3596786
{txt}{space 22} {c |}
{space 14}1.maduro {c |}{col 24}{res}{space 2}-.1367657{col 36}{space 2} .1042142{col 47}{space 1}   -1.31{col 56}{space 3}0.190{col 64}{space 4} -.341315{col 77}{space 3} .0677837
{txt}{space 22} {c |}
{space 11}Q106#maduro {c |}
{space 1}Somewhat favorable#1  {c |}{col 24}{res}{space 2} .2159583{col 36}{space 2} .1259686{col 47}{space 1}    1.71{col 56}{space 3}0.087{col 64}{space 4}-.0312903{col 77}{space 3} .4632068
{txt}{space 1}Somewhat unfavorable #{c |}
{space 20}1  {c |}{col 24}{res}{space 2} .3041053{col 36}{space 2} .1147473{col 47}{space 1}    2.65{col 56}{space 3}0.008{col 64}{space 4} .0788817{col 77}{space 3} .5293289
{txt}{space 3}Very unfavorable#1  {c |}{col 24}{res}{space 2}  .214311{col 36}{space 2} .1065644{col 47}{space 1}    2.01{col 56}{space 3}0.045{col 64}{space 4} .0051487{col 77}{space 3} .4234732
{txt}{space 22} {c |}
{space 18}Q101 {c |}{col 24}{res}{space 2} .0010389{col 36}{space 2} .0007658{col 47}{space 1}    1.36{col 56}{space 3}0.175{col 64}{space 4}-.0004642{col 77}{space 3} .0025419
{txt}{space 18}Q102 {c |}{col 24}{res}{space 2} .0012926{col 36}{space 2} .0191765{col 47}{space 1}    0.07{col 56}{space 3}0.946{col 64}{space 4}-.0363467{col 77}{space 3} .0389319
{txt}{space 18}Q103 {c |}{col 24}{res}{space 2} .0138381{col 36}{space 2} .0090021{col 47}{space 1}    1.54{col 56}{space 3}0.125{col 64}{space 4}-.0038309{col 77}{space 3} .0315072
{txt}{space 18}Q104 {c |}{col 24}{res}{space 2} .0019385{col 36}{space 2} .0011766{col 47}{space 1}    1.65{col 56}{space 3}0.100{col 64}{space 4}-.0003709{col 77}{space 3}  .004248
{txt}{space 18}Q105 {c |}{col 24}{res}{space 2}  .021644{col 36}{space 2} .0037532{col 47}{space 1}    5.77{col 56}{space 3}0.000{col 64}{space 4} .0142772{col 77}{space 3} .0290107
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .2783116{col 36}{space 2} .1060136{col 47}{space 1}    2.63{col 56}{space 3}0.009{col 64}{space 4} .0702303{col 77}{space 3} .4863929
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, dydx(violence) over(Q106)
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}       861
{txt}Model VCE{col 14}: {res}OLS

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.violence}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:over}:{space 1}{res:Q106}{p_end}
{p2colreset}{...}

{res}{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35} Delta-method
{col 23}{c |}      dy/dx{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}0.violence           {col 23}{txt}{c |}  (base outcome)
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}1.violence            {txt}{c |}
{space 17}Q106 {c |}
{space 6}Very favorable  {c |}{col 23}{res}{space 2}-.0792266{col 35}{space 2} .1039555{col 46}{space 1}   -0.76{col 55}{space 3}0.446{col 63}{space 4}-.2832682{col 76}{space 3}  .124815
{txt}{space 2}Somewhat favorable  {c |}{col 23}{res}{space 2} .1702852{col 35}{space 2} .0703423{col 46}{space 1}    2.42{col 55}{space 3}0.016{col 63}{space 4} .0322188{col 76}{space 3} .3083516
{txt}Somewhat unfavorable  {c |}{col 23}{res}{space 2} .1066956{col 35}{space 2} .0480035{col 46}{space 1}    2.22{col 55}{space 3}0.027{col 63}{space 4} .0124754{col 76}{space 3} .2009158
{txt}{space 4}Very unfavorable  {c |}{col 23}{res}{space 2} .0720062{col 35}{space 2} .0220711{col 46}{space 1}    3.26{col 55}{space 3}0.001{col 63}{space 4} .0286854{col 76}{space 3} .1153269
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 87}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. marginsplot, recast(scatter) yline(0, lcolor(gs0)) xscale(range(0.5 4.5)) xtitle("") title("") ytitle("Violence effect on support for sanctions") ///
> graphregion(color(white)) xlabel(,labsize(small)) ylabels(-0.4 (0.1) 0.4) level(90) ciopts(lcolor(gs0)) bgcolor(white)
{res}
{text}{p 2 6 2}Variables that uniquely identify margins: Q106{p_end}
{res}{txt}
{com}. 
{txt}end of do-file

{com}. exit, clear
